I've written a simple code to generate a random walk in a given graph G using the networkx library.. Now, as i take the walk, I want the edges to get colored and drawn using matplotlib.. say in a loop. Eg: say i'm walking from node 1 to node 2 from a connecting edge, I want that edge to be colored differently from the rest. Heres the code:
def unweighted_random_walk(starting_point,ending_point, graph):
'''
starting_point: String that represents the starting point in the graph
ending_point: String that represents the ending point in the graph
graph: A NetworkX Graph object
'''
##Begin the random walk
current_point=starting_point
#current_node=graph[current_point]
current_point_neighors=graph.neighbors(current_point)
hitting_time=0
#Determine the hitting time to get to an arbitrary neighbor of the
#starting point
while current_point!=ending_point:
#pick one of the edges out of the starting_node with equal probs
possible_destination=current_point_neighbors[random.randint(0,current_point_neighors)]
current_point=possible_destination
current_point_neighbors=graph.neighbors(current_point)
hitting_time+=1
return hitting_time
Here's what I use:
def colors(G):
colors = []
for edge,data in G.edges_iter(data=True):
# return a color string based on whatever property you want
return 'red' if data['someproperty'] else 'blue'
# alternatively you could store a 'color' key on the edge
# return data['color']
return colors
# When you invoke the draw command pass a list of edge colors
nx.draw_spectral(G, edge_color=colors(G))
This work fine... however, be careful to fill the list with the appropriate values. A modification to the code that works is:
def colors(G, attrib):
colors = []
for node,data in G.nodes_iter(data=True):
# return a color string based on whatever property you want
if data['someproperty'] != attrib:
colors.append('AliceBlue')
else:
colors.append('Crimson')
return colors
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